key: cord-0741956-kc7rj9je
authors: Poloni, Chad; Szyf, Moshe; Cheishvili, David; Tsoukas, Christos M
title: Are the healthy vulnerable? Cytomegalovirus seropositivity in healthy adults is associated with accelerated epigenetic age and immune-dysregulation
date: 2021-07-13
journal: J Infect Dis
DOI: 10.1093/infdis/jiab365
sha: 35455d6b688677a3ed1969ec3f18366a4e32ef0f
doc_id: 741956
cord_uid: kc7rj9je

BACKGROUND: Evaluating age as a risk factor for susceptibility to infectious diseases, particularly for COVID-19, is critical. Cytomegalovirus (CMV) serologic prevalence increases with age, and associates with inflammatory-mediated diseases in the elderly. However, little is known regarding the subclinical impact of CMV and risk it poses to healthy older adults. Prior to the COVID-19 pandemic we conducted a study to determine the association of CMV to biologic age and immune dysregulation. METHODS: Community-dwelling, healthy adults over 60 years old were evaluated using DNA methylation assays to define epigenetic age (EpiAge) and T cell immunophenotyping to assess immune dysregulation. RESULTS: All subjects were healthy and asymptomatic. Those CMV seropositive had more lymphocytes, CD8 T cells, CD28 negative T cells, decreased CD4/CD8 cell ratios, and had higher average EpiAge (65.34 years) than those CMV seronegative (59.53 years). Decreased % CD4 (p=0.003) and numbers of CD4 T cells (p=0.0199) correlated to increased EpiAge. DISCUSSION: Our novel findings distinguish altered immunity in the elderly based on CMV status. Chronic CMV infection in healthy, older adults is associated with indicators of immune dysregulation, both of which correlate to differences in EpiAge.

Age is a major risk factor for increased susceptibility to infectious diseases and decreased vaccine efficacy [1, 2] . Immune dysregulation and chronic subclinical inflammation contribute substantially to this risk [3] . Notably, dysregulation of the immune response occurs with viral infections, and was recently also described in patients with SARS-CoV-2, which disproportionately affects the elderly [4] .

Cytomegalovirus (CMV), an almost ubiquitous human herpesvirus is strongly associated with chronic subclinical inflammation, age-associated comorbidities, and immunosenescence [5, 6] . Large studies in octa and nonagenarians have linked a dysregulated immune profile to an increased two-year mortality [7] .

On the one hand, a low CD4:CD8 T-cell ratio (<1) in CMV+ individuals, helped define the immune risk phenotype (IRP), which has been associated with increased risk of all-cause mortality. [8] . On the other hand, a high CD4:CD8 T-cell ratio (>5) in CMV+ individuals has been linked to impaired physical functioning in the elderly [9] . Herpesviruses, and in particular CMV, have an ability to initiate and maintain chronic immune activation and dysregulation, characterized by a progressive oligoclonal expansion of CD4+ and CD8+ effector memory T cells (Tem) [10] . In acute viral infections, once the infection clears, these T cell populations normally contract [10] . In contrast, the Tem cell pool following CMV infection increases, creating Tem inflation and a concomitant peripheral naïve T cell decline, characterizing a state of chronic immune dysregulation [11, 12] .

Chronic viral infections can accelerate biological ageing, as determined by epigenetic changes. This was first shown in those with HIV, where an average age-acceleration of 5.2 years was described [13] .

Epigenetic age (EpiAge) was determined by measuring methylation profiles of sites in the human genome whose methylation state correlates with age [14] . The EpiAge can also be used to calculate epigenetic age acceleration, which is a measurement of the difference between the observed EpiAge and a predicted EpiAge, from a linearized control model [13] . This tool may be useful as a clinical marker of disease A c c e p t e d M a n u s c r i p t 5 progression. Additionally, hyper methylated ELOVL2 CpG islands have been shown to be a marker of ageing and cell replication in peripheral blood [15] . DNA methylation of two CpG sites proximal to the gene exhibit high correlation with age [15] . In the elderly and those with HIV, CMV seroprevalence is exceedingly high [16, 17] . It remains unclear to what extent latent CMV infection, rather than HIV, accounts for the epigenetic age acceleration, and if it predisposes to co-morbidities frequently found in ageing.

CMV-specific T cells account for a significant portion of the Tem pool in the elderly, with estimates ranging from 10-45% of the total CD8 + T and 10% of the total CD4 + T cell populations [18, 19] . These CMV-specific T cells have an altered immune phenotype, are characterized by decreased cell surface expression of CD28 and by increased expression of KLRG-1 and CD57. These markers identify cell populations that have undergone repeated antigen stimulation [20, 21] . Furthermore, CMV-specific CD8 + T cells re-express CD45RA, a marker usually seen on naïve T cells [22] . These cells have been termed effector memory re-expressing CD45RA T cells (TEMRA), and are found in increasing numbers with age in the bone marrow and peripheral blood [23] . The immunopathology contributing to the dysregulated T cell phenotype is unknown.

CMV-associated T cell alterations may have important consequences for immunosenescence, rates of ageing, and age-associated co-morbidities. Despite the challenge of identifying CMV uninfected seniors without co-morbidities, we undertook a comparative study of healthy, older CMV+ and CMV-adults to identify phenotypic and epigenetic changes associated with ageing.

Adults attending at two McGill University Health Centre (MUHC) affiliated family medicine sites for their annual healthcare evaluations were screened for enrollment. MUHC Research Institute Review Board study approval was obtained. Based on predetermined inclusion and exclusion criteria, individuals, were enrolled if they met the following inclusion criteria: age 60 years or older, in good health and A c c e p t e d M a n u s c r i p t 6 willing to provide a single 40 ml blood sample. Individuals were excluded if they were: symptomatic, had an active or known chronic infection, a history of malignancy, autoimmune disease, diabetes, cardiovascular disease, or used immune modulators at any time. Informed consent was obtained from all study participants. All individuals were examined by a physician. The healthy status was defined using a strict version of the SENIEUR protocol criteria that also excluded those with any previous cardiac events such as myocardial infarction or stroke [24] . The SENIEUR protocol was used for this study, as it was previously created to specifically limit the influence of disease and/or medication and to standardize admission criteria for immune studies in geriatric populations. Demographic, life style and clinical data were recorded.

White cell count and differential were performed on fresh blood as a standard of care. Absolute CD4 and CD8 counts were determined using the proportion of absolute lymphocytes expressing each of these surface markers. Flow cytometric analyses of lymphocyte subsets and serological assays for CMV were performed using serum and peripheral blood mononuclear cell (PBMC) samples. PBMC samples were divided in three aliquots, frozen in 10% DMSO, and stored in liquid nitrogen immediately after being drawn. Plasma was stored at -80 C for CMV serology that was determined using a qualitative anti-CMV IgG ELISA (ABCAM), with duplicates run for each sample.

Targeted DNA methylation assays: A Pearson correlation between states of methylation of cytosine/guanine sites across the genome in blood cells from publicly available Illumina450K arrays and age (GSE61496), revealed that two sites residing proximal to the ELOVL2 gene (cg16867657 and cg21572722) exhibit a strong Pearson product-moment correlation coefficient (r=0.934, p<0.0001) and (r=0.81004, p<0.0001). We developed a targeted DNA methylation assay to this region. A weighted "EpiAge" value was calculated for the 13 CGs in this region using a linear regression model based on measuring the state of DNA methylation of ELOVL2. This region describes the highest correlation with aging amongst 450,000 CpG sites included in Illumina methylation arrays, and its methylation state has been correlated with age [25] . All surface stains were done at room temperature for 30 min in the presence of human Fc block (BD Biosciences). All samples were analysed on a BD LSR Fortessa X-20 (BD Biosciences). Fluorescence data from at least 50,000 lymphocytes were acquired. Analysis of data was performed using FlowJo V10.

Strict exclusion criteria, based on the SENIEUR protocol, were used during study enrollment. Potentially confounding mild ailments were allowed. To be certain that our findings were due to CMV infection alone, a variety of statistical tests were used to both ensure there were no significant differences in these aliments between CMV+ and CMV-groups, as well as to control for these variables during significance testing.

A c c e p t e d M a n u s c r i p t 8 A two-sided Fisher's exact test was used to determine significant differences in sex and smoking status between CMV+ and CMV-groups. An unpaired two-tailed t test was used to determine significant differences in BMI and age between the CMV-and CMV+ populations. A multilinear regression model was generated to control for sex, age, weight, height, BMI, and smoking status. The least squares method was used via Prism 8, assuming a Gaussian distribution of residuals. This model was used to test for significant differences between CMV-and CMV+ populations. This model was applied to all T cell phenotyping, replacing the dependent variable for each analysis. The following parameters were analyzed using this model: CD4/CD8 T cell ratio, lymphocyte count, absolute CD4, percent CD4, absolute CD8, percent CD8, percent CD4+ CD28-, and percent CD8+ CD28-.

The same multilinear regression model was used to determine the impact of CMV status on EpiAge by imputing EpiAge as the dependent variable. Age acceleration due to CMV was calculated as previously described, where epigenetic age acceleration was defined as the difference between observed EpiAge and predicted EpiAge [13] . To generate the predicted EpiAge, a simple linear regression was created using the CMV-control population (Y=0.5527*X + 20.43), where Y is chronological age and X is EpiAge. This A c c e p t e d M a n u s c r i p t 9 equation was used to calculate predicted EpiAges for all study individuals. The difference between the predicted and actual EpiAge was calculated to produce epigenetic age acceleration values for all individuals.

A separate multilinear regression model was generated to determine the impact of EpiAge on CD4/CD8 T cell ratio, lymphocyte count, absolute CD4, percent CD4, absolute CD8, percent CD8, percent CD4+ CD28-, and percent CD8+ CD28-. The above equation was used, substituting CMV with EpiAge (β1*EpiAge).

The Bonferroni correction was used for dependent variables that were tested in both multilinear regression models. P values were considered significant at <0.025 for the following dependent variables:

CD4/CD8 T cell ratio, absolute CD4, percent CD4, absolute CD8, percent CD8, percent CD4 CD28-, and percent CD8 CD28-. All other P values were considered significant at <0.05. All significance tests were carried out using GraphPad Prism 8.

The study sponsor had no role in the study design or the collection of data.

A total of 520 individuals, sequentially presenting for annual clinical assessments, were evaluated as potential study participants. Of these, 429 were deemed not eligible because of current or past illnesses that included malignancy, autoimmune disease, diabetes, cardiovascular disease, or use of immune modulators. Of the 91 persons that met the study enrollment criteria and signed informed consent, 2 refused phlebotomy and 2, although healthy at screening were found to have active infection at the time of the blood draw. These 4 were excluded from the study and the remaining eighty-seven subjects enrolled completed the study. These individuals had minor clinical, stable conditions (hypertension, hypothyroidism, osteoporosis, dyslipidemia, benign prostatic hypertrophy, dyslipidemia, dyspepsia and depression). Ages ranged from 60-90 years old, with 65 subjects CMV+ and 22 CMV-. The two groups did not significantly differ in sex, age, BMI, and smoking status (Table 1) .

A c c e p t e d M a n u s c r i p t 10 CMV seropositive individuals had higher lymphocyte counts.

The complete blood counts carried out on each individual revealed no significant differences in red blood cell, hemoglobin, leukocyte, or neutrophil counts between the CMV+ and CMV-groups. The CMV+ group (1.88 x 10 9 cells / ml), however, had a significantly higher lymphocyte count than the CMV-group (1.49 x 10 9 cells / ml) (p=0.0112) (Fig 1a) .

CMV infection was associated with a decrease in the CD4/CD8 T cell ratio (2.85 vs 4.27, p=0.0084) (Fig   1b) . The MUHC established normal CD4/CD8 ratios are 1.8-3.4. We defined ratios of <1 indicative of relevant dysregulation based on the OCTA and NONA studies. To assess the degree of T cell phenotypic dysregulation, the CMV groups were stratified on very low <1.0, extended normal 1.1-4.9 and very high >5.0 ratios, based on the OCTA/NONA studies (ratio <1) and BELFRAIL study (ratio >5) indicating negative clinical outcomes [9, 27] . The CMV seronegative population had a lower proportion of individuals with a very low T cell ratio <1 (4.6%) compared to the seropositive population (16.9%).

The percentages of CD4 and CD8 T cells were calculated from live, CD3+ lymphocytes. There were no differences in CD4 percentage and absolute numbers between the two groups (Fig 2a) . The CMV+ had a significantly higher percentage (22.78% vs 14.64%, p=0.0034) and absolute number (0.44 x 10 9 cells/ml vs 0.22 x 10 9 cells/ml, p=0.0021) of CD8 T cells, as compared to the seronegative population (Fig 2b) . In CMV seropositives, a significant increase in the percentage of CD8+ CD28-T cells (55.02% vs 22.95%, p<0.0001) was noted (Fig 3) . There was no significant difference in the percentage of CD4+ CD28-T cells between groups. There were no significant differences in the activation markers CD38 and HLA-DR between CMV+ and CMV-.

A c c e p t e d M a n u s c r i p t 11 Samples at the time of EpiAge analysis were blinded to CMV serostatus. EpiAge was calculated for each study participant. Due to technical reasons, 14 samples failed to sequence. The CMV+ group had a significantly higher EpiAge (65.34 years) than the CMV-control group (59.53 years) (p=0.0116) (Fig. 4) .

We calculated age acceleration as previously described [13] . EpiAge (X) and chronological age (Y) in the CMV-group were plotted and the linear regression equation (Y=0.5527*X + 20.43). We then computed the residual between the regression line and EpiAge in the CMV+ group to calculate age acceleration.

The result revealed a 5.1 year age acceleration in the CMV+ group (p=0.0116) (Fig. 5) .

A multilinear regression was carried out to determine the relationships between EpiAge and absolute and % CD4, % CD4+ CD28-, absolute and % CD8, % CD8+ CD28-, CD4/CD8 ratio, and IRP. EpiAge positively correlated with decreased absolute (p=0.0199) and percent CD4 T cells (p=0.0030). Linear regressions were generated to visualize the relationship (Fig. 6 ). There were no significant associations between EpiAge and CD8 T cells. CMV was the only variable that had significant effects on T cell ratio and absolute and percent CD8.

The findings presented in this study reflect the older (60-90 years) population of Montreal, Canada. It is important to note that the study was conducted prior to the COVID-19 pandemic. Furthermore, the recruitment of healthy seniors for this study was one of the major challenges, with the screening and recruitment process starting four years prior to completion of the study. A total of 520 adults over the age of 60 were screened, with only 87 (16.7%) meeting the enrollment criteria. Of these, 25.3% were CMV-.

This highlights a common obstacle when researching CMV in the elderly. It is known that infection rates of the virus increase with age, and 74.4% of our study population was CMV+, which matches other studies [28] .

A c c e p t e d M a n u s c r i p t 12 Our analysis outperforms those done in the BEFRAIL, OCTA, and NONA studies, as all of these studies explicitly mention that unknown disease states may have been a factor in their results [9, 29, 30] . Our strict screening allowed us to produce a more robust analysis. We included sex, age, BMI, and smoking status in our multivariate linear analysis, while eliminating diabetes, malignancy, infection, immune modulating drugs, cardiovascular disease, and autoimmune disorders at enrollment using entry criteria.

We were still able to confirm the findings of the BEFRAIL, OCTA, and NONA studies, specifically an altered T cell ratio and expansion of CD8 T cells.

We found that CMV infection was associated with an increased proportion of T cell ratios of <1. As previously shown by others, low T cell ratios are largely due to an oligoclonal expansion of CMVspecific CD8 T cells [31] . Of importance, there was no decrease in the absolute number of CD4 T cells, but a significant increase in the absolute number of CD8 T cells. We have also shown an increase in the total lymphocyte count in the CMV+ group. A similar finding was noted in human renal transplant recipients and in baboons [32, 33] . In CMV+ individuals, an increase in lymphocytes is a function of age, however we show it is also a function of CMV infection, as our CMV+ group had a higher lymphocyte count than the CMV-group [34] .

The effect of CMV infection on epigenetic ageing was first described by Kananen et al, which found accelerated ageing in CMV+ young individuals between the ages of 20-30 and also in the very elderly, 90 years and over. That study only had 6 CMV-controls in the 90+ group, and did not include anyone between the ages of 60-90. Our study expands on these findings by analysing the missing age group, as well as making correlations between epigenetic age, a dysregulated T cell phenotype, and the IRP. As such, the findings have relevance regarding the use of EpiAge as a risk factor for many co-morbidities and infectious diseases. The SARS CoV-2 pandemic has highlighted the importance of mortality risk stratification based on age, where the elderly account for 20% of those infected, but 80% of deaths [35] .

A c c e p t e d M a n u s c r i p t 13 In healthy individuals over 60 numerical years of age, our model indicated an age acceleration of 5.1 years solely due to CMV infection. Previous reports have associated CMV positivity with all-cause mortality and increased risk of cardiovascular disease in the general population, highlighting the serious impacts of chronic, untreated, subclinical infection [36, 37] . This effect is amplified in those living with HIV, where the vast majority of patients have CMV co-infections, leading us to dispute a 5.2-year average-age acceleration finding attributed to HIV-1 alone, since the contribution of CMV was not considered in that study [13] . Ongoing antigenic stimulation from chronic viral infections, including CMV, results in premature T cell exhaustion and accelerated telomere shortening [38] . In a prospective large cohort study, CMV seropositivity was associated with shortened telomeres. Declines in telomere length occurred over a three year period and although the association was made with multiple herpes viruses, CMV was the main driver [39] . We have also previously demonstrated telomere shortening of lymphocytes in HIV treated individuals having an immune risk phenotype, which is characterized by CMV seropositivity and low CD4/CD8 cell ratios [26] .

Furthermore, CMV-positivity is associated with a 2.5-fold increased risk of morality in AIDS patients, with CMV DNA load being a better predictor of mortality than CD4+ count [40] . A CMV-/HIV+ population is needed to truly elucidate the age-accelerating effects of HIV. Additionally, we showed that decreased percent and absolute number of CD4 T cells were associated to increases in EpiAge, identifying potential contributors to increased EpiAge. A cohort spanning additional chronological ages is needed to accurately investigate T cell dysregulation and EpiAge.

A limitation of our study was that we did not phenotype CMV-specific T cells, rather we looked at T cell subsets as a whole. Moving forward, it is important to determine if phenotypic changes occur in CMVspecific T cells, and if changes in CMV-specific T cells are correlated with chronological and EpiAge.

In conclusion, we identified new biomarkers indicating increased epigenetic age, accelerated ageing and immune dysregulation in healthy, asymptomatic, older adults with CMV. Since the COVID-19 pandemic A c c e p t e d M a n u s c r i p t 14 has identified age as a major risk factor for infectious disease severity, our novel findings may have prognostic relevance. Additionally, we highlight the need to explore CMV vaccinations and prophylaxis with antiviral drugs, such as letermovir and valganciclovir, which have both been shown to reduce CMV infection and CD8 T cell activation in the case of the later [41, 42] . Further studies are needed to determine these proposed interventions with respect to their potential clinical significance and effect on EpiAge. 

A two-sided Fisher's exact test was used to determine significant differences in sex and smoking status between CMV+ (n=65) and CMV-(n=22). An unpaired two-tailed t test was used to determine significant differences in BMI and age between CMV+ and CMV-populations. P-values below 0.5 were considered significant. The ratios, percentages, and absolute numbers of CD4 and CD8 T cells were determined for each participant using flow cytometry (A+B). The CMV+ (n=65) and CMV-(n=22) populations were compared using multivariable linear regression models including age, sex, smoking status, and BMI as covariables. A Bonferroni correction was applied, and p-values below 0.025 were considered significant.

A c c e p t e d M a n u s c r i p t 22 Figure 3 . The CD8 T cell phenotype is altered in CMV-infected participants.

Peripheral blood mononuclear cells were isolated from CMV-and CMV+ individuals. Flow cytometry was used to phenotype CD3-positive T cells from each individual participant, specifically analyzing CD4, CD8, and CD28. The proportions of CD28 for CMV-(n=22) and CMV+ (n=65) were calculated for CD4 and CD8 -positive T cells. Multivariable linear regression models were used to test for significance including age, sex, smoking status, and BMI as covariables. A Bonferroni correction was applied, and p-values below 0.025 were considered significant.

DNA was isolated from PBMCs of each sample and the methylation status near the Elov12 gene was measured using bisulfite-sequencing. An EpiAge was calculated for each participant, and the CMV-(n=21) and CMV+ (n=54) groups were compared using a multilinear regression analysis including age, sex, smoking status, and BMI as covariables. A violin plot was generated for each group, with the median and quartiles represented by dashed lines. P-values below 0.05 were considered significant.

The age acceleration due to CMV infection was determined by calculating the difference in the experimental EpiAge and predicted EpiAge. The predicted EpiAge was generated from a linear model based on the control CMV-group. The predicted (blue) and actual (green) EpiAges were plotted against chronological age for CMV-and CMV+ populations, and simple linear regressions A c c e p t e d M a n u s c r i p t 23 were generated to visualize the relationship. Age acceleration was calculated for both CMV-(n=21) and CMV+ (n=54) groups, by calculating the difference between the predicted and actual EpiAges.

P-values below 0.05 were considered significant. Smoking Status 0 (0%) 5 (6.8%) 0.32 Table 1 CMV- 

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We would like to thank Louise Gilbert, and Debbie Cutler, for technical support. 

CT conceived and supervised the study. CT and MS designed the experiments, reviewed data, and the analysis of results. CP did the immune assays, analyzed the data, and prepared all figures. DC conducted the epigenetic studies. CT recruited and enrolled study participants. CP collected, processed blood